Skip to main content

Terms and Conditions

 Terms and Conditions of Salim Wireless


Below are the Terms and Conditions for use of https://www.salimwireless.com.


Please read these carefully. If you need to contact us regarding any aspect of the following terms of use of our website, please contact us at iamsalim002@gmail.com


By accessing the content of Salim Wireless ( hereafter referred to as a website ) you agree to the terms and conditions set out herein and also accept our privacy policy. If you do not agree to any of the terms and conditions you should not continue to use the website and leave immediately.


You agree that you shall not use the website for any illegal purposes and that you will respect all applicable laws and regulations.


You agree not to use Salim Wireless! website in a way that may impair the performance, corrupt or manipulate the content or information available on the website or reduce the overall functionality of the website.


You agree not to compromise the security of the website or attempt to gain access to secured areas of the website or attempt to access any sensitive information you may believe exist on the website or server where it is hosted.


You agree to be fully responsible for any claim, expense, losses, liability, costs including legal fees incurred by us arising from any infringement of the terms and conditions in this agreement and to which you will have agreed if you continue to use the website.


The reproduction, distribution in any method whether online or offline is strictly not prohibited. The work on the website and the images, logos, text and other such information is not the property of https://www.salimwireless.com ( unless otherwise stated ).


Disclaimer


Though we strive to be completely accurate in the information that is presented on our site and attempt to keep it as up to date as possible, in some cases, some of the information you find on the website may be slightly outdated.


Salim Wireless reserves the right to make any modifications or corrections to the information you find on the website at any time without notice.


Change to the Terms and Conditions of Use


We reserve the right to make changes and to revise the above-mentioned Terms and Conditions of use.


Last Revised: 21-05-2022

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

Constellation Diagrams of ASK, PSK, and FSK

📘 Overview of Energy per Bit (Eb / N0) 🧮 Online Simulator for constellation diagrams of ASK, FSK, and PSK 🧮 Theory behind Constellation Diagrams of ASK, FSK, and PSK 🧮 MATLAB Codes for Constellation Diagrams of ASK, FSK, and PSK 📚 Further Reading 📂 Other Topics on Constellation Diagrams of ASK, PSK, and FSK ... 🧮 Simulator for constellation diagrams of m-ary PSK 🧮 Simulator for constellation diagrams of m-ary QAM BASK (Binary ASK) Modulation: Transmits one of two signals: 0 or -√Eb, where Eb​ is the energy per bit. These signals represent binary 0 and 1.    BFSK (Binary FSK) Modulation: Transmits one of two signals: +√Eb​ ( On the y-axis, the phase shift of 90 degrees with respect to the x-axis, which is also termed phase offset ) or √Eb (on x-axis), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BPSK (Binary PSK) Modulation: Transmits one of two signals...

Online Simulator for ASK, FSK, and PSK

Try our new Digital Signal Processing Simulator!   Start Simulator for binary ASK Modulation Message Bits (e.g. 1,0,1,0) Carrier Frequency (Hz) Sampling Frequency (Hz) Run Simulation Simulator for binary FSK Modulation Input Bits (e.g. 1,0,1,0) Freq for '1' (Hz) Freq for '0' (Hz) Sampling Rate (Hz) Visualize FSK Signal Simulator for BPSK Modulation ...

Fading : Slow & Fast and Large & Small Scale Fading

📘 Overview 📘 LARGE SCALE FADING 📘 SMALL SCALE FADING 📘 SLOW FADING 📘 FAST FADING 🧮 MATLAB Codes 📚 Further Reading LARGE SCALE FADING The term 'Large scale fading' is used to describe variations in received signal power over a long distance, usually just considering shadowing.  Assume that a transmitter (say, a cell tower) and a receiver  (say, your smartphone) are in constant communication. Take into account the fact that you are in a moving vehicle. An obstacle, such as a tall building, comes between your cell tower and your vehicle's line of sight (LOS) path. Then you'll notice a decline in the power of your received signal on the spectrogram. Large-scale fading is the term for this type of phenomenon. SMALL SCALE FADING  Small scale fading is a term that describes rapid fluctuations in the received signal power on a small time scale. This includes multipath propagation effects as well as movement-induced Doppler fr...

Theoretical BER vs SNR for m-ary PSK and QAM

Relationship Between Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) The relationship between Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) is a fundamental concept in digital communication systems. Here’s a detailed explanation: BER (Bit Error Rate): The ratio of the number of bits incorrectly received to the total number of bits transmitted. It measures the quality of the communication link. SNR (Signal-to-Noise Ratio): The ratio of the signal power to the noise power, indicating how much the signal is corrupted by noise. Relationship The BER typically decreases as the SNR increases. This relationship helps evaluate the performance of various modulation schemes. BPSK (Binary Phase Shift Keying) Simple and robust. BER in AWGN channel: BER = 0.5 × erfc(√SNR) Performs well at low SNR. QPSK (Quadrature...

DFTs-OFDM vs OFDM: Why DFT-Spread OFDM Reduces PAPR Effectively

DFT-spread OFDM (DFTs-OFDM) has lower Peak-to-Average Power Ratio (PAPR) because it "spreads" the data in the frequency domain before applying IFFT, making the time-domain signal behave more like a single-carrier signal rather than a multi-carrier one like OFDM. Deeper Explanation: Aspect OFDM DFTs-OFDM Signal Type Multi-carrier Single-carrier-like Process IFFT of QAM directly QAM → DFT → IFFT PAPR Level High (due to many carriers adding up constructively) Low (less fluctuation in amplitude) Why PAPR is High Subcarriers can add in phase, causing spikes DFT "pre-spreads" data, smoothing it Used in Wi-Fi, LTE downlink LTE uplink (as SC-FDMA) In OFDM, all subcarriers can...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

📘 Overview of BER and SNR 🧮 Online Simulator for BER calculation of m-ary QAM and m-ary PSK 🧮 MATLAB Code for BER calculation of M-ary QAM, M-ary PSK, QPSK, BPSK, ... 📚 Further Reading 📂 View Other Topics on M-ary QAM, M-ary PSK, QPSK ... 🧮 Online Simulator for Constellation Diagram of m-ary QAM 🧮 Online Simulator for Constellation Diagram of m-ary PSK 🧮 MATLAB Code for BER calculation of ASK, FSK, and PSK 🧮 MATLAB Code for BER calculation of Alamouti Scheme 🧮 Different approaches to calculate BER vs SNR What is Bit Error Rate (BER)? The abbreviation BER stands for Bit Error Rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. BER = (number of bits received in error) / (total number of tran...

Theoretical BER vs SNR for binary ASK, FSK, and PSK

📘 Overview & Theory 🧮 MATLAB Codes 📚 Further Reading Theoretical BER vs SNR for Amplitude Shift Keying (ASK) The theoretical Bit Error Rate (BER) for binary ASK depends on how binary bits are mapped to signal amplitudes. For typical cases: If bits are mapped to 1 and -1, the BER is: BER = Q(√(2 × SNR)) If bits are mapped to 0 and 1, the BER becomes: BER = Q(√(SNR / 2)) Where: Q(x) is the Q-function: Q(x) = 0.5 × erfc(x / √2) SNR : Signal-to-Noise Ratio N₀ : Noise Power Spectral Density Understanding the Q-Function and BER for ASK Bit '0' transmits noise only Bit '1' transmits signal (1 + noise) Receiver decision threshold is 0.5 BER is given by: P b = Q(0.5 / σ) , where σ = √(N₀ / 2) Using SNR = (0.5)² / N₀, we get: BER = Q(√(SNR / 2)) Theoretical BER vs ...

Kalman Filter: Mathematical Description and Example

Kalman Filter: Mathematical Description 1. System Model (State-Space Representation) State Equation \[ \mathbf{x}_{k} = \mathbf{F}_{k-1}\mathbf{x}_{k-1} + \mathbf{B}_{k-1}\mathbf{u}_{k-1} + \mathbf{w}_{k-1} \] Measurement Equation \[ \mathbf{z}_{k} = \mathbf{H}_{k}\mathbf{x}_{k} + \mathbf{v}_{k} \] where: \(\mathbf{x}_k\): system state vector \(\mathbf{u}_k\): control input \(\mathbf{z}_k\): measurement vector \(\mathbf{F}_k\): state transition matrix \(\mathbf{B}_k\): control input matrix \(\mathbf{H}_k\): observation matrix \(\mathbf{w}_k \sim \mathcal{N}(0,\mathbf{Q}_k)\): process noise \(\mathbf{v}_k \sim \mathcal{N}(0,\mathbf{R}_k)\): measurement noise 2. Kalman Filter Assumptions Linear system dynamics Gaussian, white,...